Gomez, Daniel and Montero, Javier
(2008)
*Fuzzy sets in remote sensing classification.*
Soft Computing, 12
.
pp. 243-249.
ISSN 1432-7643

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## Abstract

Supervised classification in remote sensing is a very complex problem and involves steps of different nature, including a serious data preprocessing. The final objective can be stated in terms of a classification of isolated pixels between classes, which can be either previously known or not (for example, different land uses), but with no particular shape nither well defined borders. Hence, a fuzzy approach seems natural in order to capture the structure of the image. In this paper we stress that some useful tools for a fuzzy classification can be derived from fuzzy coloring procedures, to be extended in a second stage to the complete non visible spectrum. In fact, the image is considered here as a fuzzy graph defined on the set of pixels, taking advantage of fuzzy numbers in order to summarize information. A fuzzy model is then presented, to be considered as a decision making aid tool. In this way we generalize the classical definition of fuzzy partition due to Ruspini, allowing in addition a first evaluation of the quality of the classification in this way obtained, in terms of three basic indexes (measuring covering, relevance and overlapping of our family of classes).

Item Type: | Article |
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Uncontrolled Keywords: | Fuzzy classification systems; Remote sensing; Fuzzy graph |

Subjects: | Sciences > Mathematics > Mathematical statistics |

ID Code: | 16297 |

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Deposited On: | 10 Sep 2012 09:45 |

Last Modified: | 19 Apr 2016 17:03 |

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